The OML4R package OREmodels contains functions with which you can create advanced analytical data models using ore.frame objects.

These functions are described in the following topics:

• About OREmodels Functions
  The OREmodels package contains functions with which you can build machine learning models using ore.frame objects.
• About the longley Data Set for Examples
  Most of the linear regression and ore.neural examples use the longley data set, which is provided by R.
• Build Linear Regression Models
  The ore.lm and ore.stepwise functions perform least squares regression and stepwise least squares regression, respectively, on data represented in an ore.frame object.
• Build a Generalized Linear Model
  The ore.glm functions fits generalized linear models on data in an ore.frame object..
• Build a Neural Network Model
  Neural network models can be used to capture intricate nonlinear relationships between inputs and outputs or to find patterns in data.
• Build a Random Forest Model
  The ore.randomForest function provides an ensemble learning technique for classification of data in an ore.frame object.